Research on Fuzzy Association Classification Algorithm for Large Transaction Database Based on SVM
- Wen-qi Wang, Qiang Li
- Corresponding Author
- Wen-qi Wang
Available Online March 2014.
- https://doi.org/10.2991/icieac-14.2014.3How to use a DOI?
- classification; decision tree;SVM; eigenvector;
- Aiming at the defects of inefficiency and hard classification boundary in large transaction database classification, A. fuzzy associative classification algorithm based on SVM was proposed, SVM input eigenvector was constructed by weighed index and compatibility measure of fuzzy associative classification role, the effect of quantitative attribute discretization on association classifier was effectively reduced. With reference to decision tree classification algorithm, linear kernel function was used to make the speed of classification because of classification of the test samples are not complete decision tree traversal, and adjustment of parameters when used the nonlinear kernel function was avoided. Experimental results verify the feasibility and effectiveness of the algorithm.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Wen-qi Wang AU - Qiang Li PY - 2014/03 DA - 2014/03 TI - Research on Fuzzy Association Classification Algorithm for Large Transaction Database Based on SVM BT - 2nd International Conference on Information, Electronics and Computer PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/icieac-14.2014.3 DO - https://doi.org/10.2991/icieac-14.2014.3 ID - Wang2014/03 ER -